Thesis (Ph. D.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 91-107).

Thesis (Ph.D.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 91-107) Also available in print.

Thesis (M.S.)--West Virginia University, 2005. / Title from document title page. Document formatted into pages; contains viii, 91 p. : ill. (some col.), col. map. Includes abstract. Includes bibliographical references (p. 67-69).

Early detection of disease and insect infestation within crops and precise application of pesticides can help reduce potential production losses, reduce environmental risk, and reduce the cost of farming. The goal of this study was the advanced detection of early blight (Alternaria solani) in potato (Solanum tuberosum) plants using hyperspectral remote sensing data captured with a handheld spectroradiometer. Hyperspectral reflectance spectra were captured 10 times over five weeks from plants grown to the vegetative and tuber bulking growth stages. The spectra were analyzed using principal component analysis (PCA), spectral change (ratio) analysis, partial least squares (PLS), cluster analysis, and vegetative indices. PCA successfully distinguished more heavily diseased plants from healthy and minimally diseased plants using two principal components. Spectral change (ratio) analysis provided wavelengths (490-510, 640, 665-670, 690, 740-750, and 935 nm) most sensitive to early blight infection followed by ANOVA results indicating a highly significant difference (p < 0.0001) between disease rating group means. In the majority of the experiments, comparisons of diseased plants with healthy plants using Fisher’s LSD revealed more heavily diseased plants were significantly different from healthy plants. PLS analysis demonstrated the feasibility of detecting early blight infected plants, finding four optimal factors for raw spectra with the predictor variation explained ranging from 93.4% to 94.6% and the response variation explained ranging from 42.7% to 64.7%. Cluster analysis successfully distinguished healthy plants from all diseased plants except for the most mildly diseased plants, showing clustering analysis was an effective method for detection of early blight. Analysis of the reflectance spectra using the simple ratio (SR) and the normalized difference vegetative index (NDVI) was effective at differentiating all diseased plants from healthy plants, except for the most mildly diseased plants. Of the analysis methods attempted, cluster analysis and vegetative indices were the most promising. The results show the potential of hyperspectral remote sensing for the detection of early blight in potato plants.

Fusarium graminearum is a major fungal pathogen of wheat and other small grain cereal crops globally, causing Fusarium ear blight (FEB) disease. Like many other plant pathogens, F. graminearum is predicted to produce in planta secreted effector proteins that modulate plant metabolism to suppress or re-programme plant defences. Understanding the molecular functions of Fg effectors will help to elucidate the processes underlying wheat spike colonisation and fungal pathogenicity. With the aim of identifying Fg effector proteins that can suppress host plant defences, I selected using next generation sequencing and bioinformatic analysis, a set of small secreted proteins (SSP) to express in planta using the Barley stripe mosaic virus over-expression system (BSMV-VOX). I then tested whether expression of any of these SSPs enhanced Fg fungal infection of susceptible wheat spikes. Amongst the set of Fg SSP tested, FgSSP8, which encodes a ribonuclease protein, induced strong symptoms of necrosis in N. benthamiana leaves when infiltrated via the BSMV:FgSSP8. Three other genes tested (FgSSP7, FgSSP6 and FgSSP5) enhance FEB disease formation in the majority of the experiments when overexpressed in wheat ears prior to infecting with F. graminearum. FgSSP6 and FgSSP7 belong to the cerato-platanin protein (CPP) family. In several other plant pathogenic fungi, CPPs have been implicated in a number of virulence and plant protection mechanisms, including induction of host plant cell death, binding specific polymers and/or expansin-like activity. FgSSP5 encodes a protein that possesses the pfam domain RALF (Rapid alkalinization factor; PF05498.6). RALF domain-containing proteins are predominately found in plants and play a role in plant development regulating tissue expansion and/or negatively regulating pollen tube elongation. BLAST analyses identified RALF domain containing proteins in a restricted range of different pathogen species. Based on the VOX results and biochemical tests, our hypothesis is that pre-elevated cerato-platanins (FgSSP6 and FgSSP7) levels in the apoplast/surrounding the hyphae could initially shield the hyphae from detection by the plant, but late induce an intense defence response culminating in cell death to benefit the necrotrophic phase of Fg by increasing nutrient availability. FgSSP5 may be a specific virulence factor that manipulates a key plant process, by alkalinising the plant environment during infection, and using the same plant receptor repertoire used to recognise plant proteins. Once the mechanisms are further understood, these genes/proteins could potentially be novel intervention targets either for conventional chemistries and/or for methods such as host-induced gene silencing to achieve FEB disease and/or mycotoxin control. The characterisation of single and double gene deletion F. graminearum mutants is in progress.

Cotton (Gossypium hirsutum) growth, development, and yield can be limited due to reniform nematode and bacterial blight infestation. Studies were conducted in 2016 and 2017 to evaluate the profitability of a soil fumigant application, seed treatments, and inurrow nematicides to protect cotton from nematode infestation as well as inoculation of bacterial blight at various growth stages in cotton to determine effects on yield. Research was conducted by applying various combinations of nematicides to cottonseed at planting and a fumigant prior to planting. Bacterial blight was conducted by inoculated on cotton at multiple growth stages throughout the year. Based on the results of these studies, a seed treatment plus inurrow application should be applied at planting in nematode infested fields to increase yield and economic returns in cotton. Bacterial blight infestation was greatest when inoculated at pinhead square in cotton.

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<p> This thesis seeks to describe and explain the spatial pattern of urban residential blight. The empirical analysis is limited to one study area; that of the Chicago metropolitan area. The data are U.S. Census data for census tracts in 1940, 1950, and 1960. Following a review of pertinent literature, an attempt is made to conceptualise the process that generates residential blight. From this conceptual framework, a number of hypotheses are developed concerning the relationship between residential blight and selected socio-economic variables. Other relationships are derived from an interpretation of maps of residential blight in the Chicago area for the different time periods. The hypotheses are tested using such multivariate procedures as principal components analysis, and regression and correlation analysis. The thesis also contains an application of the Blalock-Simon procedure for causal modelling to the Chicago data. The findings of the empirical analysis are related to present knowledge concerning urban residential blight. </p> / Thesis / Doctor of Philosophy (PhD)